Agent-native

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One booking service, three different claims

This constructed example separates labels that are often used together.

Description	What it tells you about the booking service
AI-native	AI is central to how the service performs its work, such as interpreting requests and handling scheduling exceptions.
Agent-native	Agents are intended users: availability, actions, permissions and results are designed to be usable by software.
Agent-ready	A stated interaction works with an agent—for example, reading available times—but other actions may remain unsupported.

These claims can overlap. They are not successive levels on an agreed maturity ladder.

Follow one request all the way through

Suppose an agent is helping arrange an equipment inspection. It needs more than a list of appointment times. The service should make clear what information is required, who can confirm a booking and how the agent can tell whether a request succeeded.

If confirmation times out, the agent needs a way to inspect the existing booking rather than unknowingly reserve another slot. This is an illustrative design requirement, not a claim that a particular provider or AE implements the workflow.

An agent clicking through a human website demonstrates the agent’s ability to use that interface. It does not establish that the service was designed around agents.

Always name what is native

Builder.io uses the label for an application framework; Vercel uses it in describing a team’s way of working. Those are different subjects. When a business claims to be agent-native, ask which service or process it means and what agents can actually do there.

The useful evidence is the supported interaction, its limits and its observed result. The label alone establishes neither reliability nor demand.